Vitality Theory for Biodemography Submitted by James Anderson to NIA February 2013 Project Summary/Abstract The project will develop a new approach to describe mortality in terms of time and age varying interactions of intrinsic physiological and extrinsic environmental processes. The approach is an extension of a two-process model that characterizes mortality patterns in terms of the loss of vitality (an abstract measure of survival capacity) through an intrinsic stochastic rate of loss of vitality and random extrinsic vitality challenges. The expected outcome of the research is a theoretical framework and tractable model that synthesizes as special cases several existing and currently incongruent paradigms of mortality. The expected impact is a new perspective and quantification of biodemographic phenomena (e.g. mortality accelerations and plateaus, heterogeneity, gene-environment interactions) in terms of the interaction of age-declining physiological survival capacity with age/time varying patterns in the magnitude and frequency of extrinsic challenges to survival capacity (e.g. acute disease, accidents, environmental stress). Specific tasks are: I. Develop an individual based vitality model and fitting algorithm. II. Demonstrate model utility through applications to issues in biodemography: A. Evolution of lifespan: inheritance of initial vitality will be tested with 1. Animal studies of longevity 2. Longevity correlations in human twin data 3. Longevity and survival rectangularization correlations with genetics B. Interpret the following phenomenon in terms of extrinsic challenge patterns 1. Frailly model generation of mortality plateaus 2. Medfly density-dependent effects on mortality 3. Reproduction and mortality tradeoffs in animal populations 4. Human epidemiological transitions The long-term goals is to promote a paradigm: 1) suitable for quantitatively characterizing genetic, behavioral and environmental contributions to mortality, 2) that can separate physiological and environmental contributions to historical mortality and 3) can be used to predict future mortality patterns contingent on a population's physiological status and expected patterns of future environmental conditions (climate, health resource, disease prevalence, food resources, social-economic patterns).